standard deviation for Gaussian kernel. The standard
deviations of the Gaussian filter are given for each axis as a
sequence, or as a single number, in which case it is equal for
all axes.

order : {0, 1, 2, 3} or sequence from same set, optional

The order of the filter along each axis is given as a sequence
of integers, or as a single number. An order of 0 corresponds
to convolution with a Gaussian kernel. An order of 1, 2, or 3
corresponds to convolution with the first, second or third
derivatives of a Gaussian. Higher order derivatives are not
implemented

output : array, optional

The output parameter passes an array in which to store the
filter output.

mode : {‘reflect’,’constant’,’nearest’,’mirror’, ‘wrap’}, optional

The mode parameter determines how the array borders are
handled, where cval is the value when mode is equal to
‘constant’. Default is ‘reflect’

cval : scalar, optional

Value to fill past edges of input if mode is ‘constant’. Default
is 0.0

Notes

The multi-dimensional filter is implemented as a sequence of
one-dimensional convolution filters. The intermediate arrays are
stored in the same data type as the output. Therefore, for output
types with a limited precision, the results may be imprecise
because intermediate results may be stored with insufficient
precision.